Precipitation and runoff variation characteristics in typical regions of North China Plain: a case study of Hengshui City

Abstract

Climate change and human activities have intensified the contradiction between water supply and demand and worsen the status of water security in North China Plain in the recent years. A study has been conducted for the evaluation of trends in hydro-meteorological variables and their response to runoff to understand the changing pattern of water resources in Hengshui City, located in the North China Plain. The inverse distance weighting interpolation, nonparametric Mann-Kendall (MK) test, Sen’s slope estimator, and wavelet analysis methods were used to assess the spatiotemporal changes in precipitation and runoff for the period 1963–2013. Besides, MK mutation point test and sequential clustering method were used to identify the mutation points of annual runoff sequence. Finally, rescaled range analysis, fractal dimension approximation, and power spectrum exponent estimation were used to predict the possible future annual runoff trends. The results revealed that average annual precipitation of Hengshui City was decreasing from its long-term average of 508.65 mm. The seasonal precipitation showed an increase in spring and autumn and a decrease in summer and winter. The precipitation of the city has a periodicity of 29, 17, and 6–7 years, among which 29 years is the main cycle. Analysis of river flow data revealed that the surface water resources in the central area are relatively short. The annual runoff in six out of eight rivers flowing through the vicinity of the city showed a downward trend while the rest two showed an upward trend. A periodicity in annual runoff of the main rivers was also observed. The mutation points in inflow series of different rivers were found to vary between 1968 and 1983. Future projections of runoff revealed both increase and decrease in flow of different rivers. The findings of the study can be used for water resources management and adaptation to climate change.